In his latest book, Foundations of Multidimensional and Metric Data Structures, Hanan Samet, renowned authority on this topic, presents a comprehensive view of spatial data structures and indexing that includes some of his own major algorithms, as well as those of other computer scientists. He is considered an expert in the use of hierarchical data structures, such as the quadtree, which is often used to partition a two-dimensional space by recursively subdividing it into four quadrants, thereby providing a means to index the data that they span.
The book is the result of Samet’s longtime research at the University of Maryland’s Computer Vision Laboratory investigating the applicability of his work to geographic information systems, computer graphics, image processing, image databases, and visualization. It was an award winner in the 2006 Best Book in Computer and Information Science competition from the Professional and Scholarly Publishers Group of the American Publishers Association.
At the Computer Vision Laboratory, Samet leads a number of research projects on the use of hierarchical data structures in GIS. His research on the integration of spatial and nonspatial data into a DBMS has resulted in the development of two systems by his research group: QUILT, a GIS based on spatial data structures such as quadtrees and octrees, and Spatial and Nonspatial Data (SAND), which integrates spatial and nonspatial data and enables browsing through a spatial database using a graphical user interface.
He has also been developing the Spatio-Textual Extraction on the Web Aiding the Retrieval of Documents system, a spatiotextual document search engine that enables the retrieval of documents on the basis of spatial proximity as well as matching keywords, which has been used for documents of the research division of the U.S. Department of Housing and Urban Development.
Foundations of Multidimensional and Metric Data Structures, part of the Morgan Kaufmann Series in Computer Graphics, is published by Morgan Kaufmann (ISBN-13: 978-0123694461; 2006; 1,024 pages) and is available from Elsevier for $64.95.